USL/UDA ReID. We follow most of the default settings in [1]}. USL ReID and UDA ReID share the same training settings in this paper, and the only difference is that the models for UDA ReID need to be first pre-trained on source datasets before training in an unsupervised manner on target datasets. The maximum distance \(d\)  between two samples is set to 0.6 and 0.7 for Market1501 and MSMT17, respectively. We use SGD optimizer to train ViTs for 50 epochs. The initial learning rate is set to 3.5e-4, and is reduced 10 times for every 20 epochs. Each mini-batch contains 256 images of 32 person IDs, each ID contains 8 images. The rate of stochastic depth is set 0.3.
